package cn.ocars.playgame.pencilstudy.services

import android.content.Context
import android.graphics.Bitmap
import android.graphics.Canvas
import android.graphics.Color
import android.graphics.Paint
import android.util.Log
import cn.ocars.playgame.pencilstudy.model.Stroke
import cn.ocars.playgame.pencilstudy.model.StrokePoint
import kotlinx.coroutines.Dispatchers
import kotlinx.coroutines.withContext
import java.util.concurrent.TimeUnit
import kotlin.random.Random

/**
 * 多模态Gemma模型识别服务
 * 使用Google Edge AI的多模态Gemma模型对用户书写笔迹进行评分
 */
class MultimodalGemmaRecognitionService(private val context: Context) {
    private val TAG = "MultimodalGemmaRecognition"
    
    // 模拟模型初始化状态
    private var isModelInitialized = false
    
    /**
     * 初始化多模态Gemma模型
     */
    suspend fun initialize() {
        withContext(Dispatchers.IO) {
            try {
                // 在实际应用中，这里会加载和初始化多模态Gemma模型
                // 例如：model = MultiModalGemma.load(context, "multimodal-gemma-3.0-lite")
                
                // 模拟模型加载过程
                Log.d(TAG, "正在加载多模态Gemma模型...")
                TimeUnit.MILLISECONDS.sleep(500) // 模拟加载时间
                
                isModelInitialized = true
                Log.d(TAG, "多模态Gemma模型加载完成")
            } catch (e: Exception) {
                Log.e(TAG, "初始化多模态Gemma模型失败", e)
                isModelInitialized = false
            }
        }
    }
    
    /**
     * 释放模型资源
     */
    fun release() {
        if (isModelInitialized) {
            // 在实际应用中，这里会释放模型资源
            // 例如：model.close()
            
            isModelInitialized = false
            Log.d(TAG, "多模态Gemma模型资源已释放")
        }
    }
    
    /**
     * 识别并评分用户书写的汉字
     * @param character 目标汉字
     * @param strokes 用户书写的笔画数据
     * @return 评分结果，包含总分、置信度、笔画评分等
     */
    suspend fun recognizeAndScore(character: String, strokes: List<Stroke>): RecognitionResult {
        return withContext(Dispatchers.IO) {
            if (!isModelInitialized) {
                Log.w(TAG, "模型未初始化，尝试重新初始化")
                initialize()
            }
            
            if (!isModelInitialized) {
                return@withContext RecognitionResult(
                    character = character,
                    totalScore = 0f,
                    confidence = 0f,
                    strokeScores = emptyList(),
                    feedback = "模型初始化失败，无法进行评分"
                )
            }
            
            try {
                // 将笔画数据转换为位图
                val bitmap = convertStrokesToBitmap(strokes)
                
                // 在实际应用中，这里会使用多模态Gemma模型进行评分
                // 例如：val result = model.recognizeAndScore(bitmap, character)
                
                // 模拟模型推理过程
                Log.d(TAG, "正在使用多模态Gemma模型对'$character'进行评分...")
                TimeUnit.MILLISECONDS.sleep(800) // 模拟推理时间
                
                // 生成模拟评分结果
                val (totalScore, confidence, strokeScores) = generateMockScores(character, strokes)
                
                // 生成反馈意见
                val feedback = generateFeedback(character, totalScore, strokeScores)
                
                Log.d(TAG, "评分完成: 总分=$totalScore, 置信度=$confidence")
                
                RecognitionResult(
                    character = character,
                    totalScore = totalScore,
                    confidence = confidence,
                    strokeScores = strokeScores,
                    feedback = feedback
                )
            } catch (e: Exception) {
                Log.e(TAG, "评分过程中发生错误", e)
                RecognitionResult(
                    character = character,
                    totalScore = 0f,
                    confidence = 0f,
                    strokeScores = emptyList(),
                    feedback = "评分过程中发生错误: ${e.message}"
                )
            }
        }
    }
    
    /**
     * 将笔画数据转换为位图
     */
    private fun convertStrokesToBitmap(strokes: List<Stroke>): Bitmap {
        // 创建一个空白位图
        val bitmap = Bitmap.createBitmap(256, 256, Bitmap.Config.ARGB_8888)
        val canvas = Canvas(bitmap)
        
        // 设置背景为白色
        canvas.drawColor(Color.WHITE)
        
        // 设置画笔
        val paint = Paint().apply {
            color = Color.BLACK
            strokeWidth = 8f
            isAntiAlias = true
            style = Paint.Style.STROKE
            strokeCap = Paint.Cap.ROUND
            strokeJoin = Paint.Join.ROUND
        }
        
        // 绘制所有笔画
        for (stroke in strokes) {
            if (stroke.points.isNotEmpty()) {
                val path = android.graphics.Path()
                path.moveTo(stroke.points[0].x, stroke.points[0].y)
                
                for (i in 1 until stroke.points.size) {
                    path.lineTo(stroke.points[i].x, stroke.points[i].y)
                }
                
                canvas.drawPath(path, paint)
            }
        }
        
        return bitmap
    }
    
    /**
     * 生成模拟评分结果
     */
    private fun generateMockScores(character: String, strokes: List<Stroke>): Triple<Float, Float, List<Float>> {
        // 基于字符和笔画数生成不同的评分
        val baseScore = when (character) {
            "一" -> 0.9f
            "二" -> 0.85f
            "三" -> 0.8f
            "十" -> 0.75f
            "人" -> 0.7f
            "大" -> 0.65f
            "小" -> 0.6f
            "中" -> 0.55f
            "上" -> 0.5f
            "下" -> 0.45f
            else -> 0.7f
        }
        
        // 添加随机波动
        val randomFactor = Random.nextFloat() * 0.2f - 0.1f // -0.1 到 0.1
        val totalScore = (baseScore + randomFactor).coerceIn(0f, 1f)
        
        // 置信度通常略高于总分
        val confidence = (totalScore + Random.nextFloat() * 0.1f).coerceIn(0f, 1f)
        
        // 为每个笔画生成评分
        val strokeScores = List(strokes.size) { index ->
            val strokeBaseScore = totalScore + (Random.nextFloat() * 0.2f - 0.1f)
            strokeBaseScore.coerceIn(0f, 1f)
        }
        
        return Triple(totalScore, confidence, strokeScores)
    }
    
    /**
     * 生成反馈意见
     */
    private fun generateFeedback(character: String, totalScore: Float, strokeScores: List<Float>): String {
        return when {
            totalScore >= 0.9f -> "非常棒！'$character'字写得非常标准，继续保持！"
            totalScore >= 0.7f -> "写得不错！'$character'字的基本结构正确，可以再注意一下细节。"
            totalScore >= 0.5f -> "还可以！'$character'字的大致形状已经出来了，但需要多加练习。"
            else -> "继续努力！'$character'字需要多练习，注意观察标准字形的结构。"
        }
    }
    
    /**
     * 评分结果数据类
     */
    data class RecognitionResult(
        val character: String,           // 目标汉字
        val totalScore: Float,           // 总分 (0-1)
        val confidence: Float,           // 置信度 (0-1)
        val strokeScores: List<Float>,   // 每个笔画的评分 (0-1)
        val feedback: String             // 反馈意见
    )
}